基于1-bit压缩感知非凸算法的平面ECT图像重建

doi:10.3969/j.issn.1000-1158.2024.12.07

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Abstract In order to improve the imaging quality of planar capacitance imaging system, a planar ECT image reconstruction method based on 1-bit compressed sensing (1-bit CS) non convex algorithm is proposed. Firstly, discrete cosine basis (DCT) is used to sparsely represent grayscale values.Secondly, the maximum minimum concave penalty (MCP) is introduced as the regularization term, and the 1-bit CS MCP regularization model is established. Then, the near end operator of the dual solution is iteratively updated using the MCP non convex algorithm to obtain the optimal dual solution. Finally, calculate the reconstructed grayscale values based on the dual solution and perform image reconstruction. The simulation and experimental results show that compared with Tikhonov algorithm, Landweber algorithm and traditional compressed sensing algorithm, the average relative error and correlation coefficient of the reconstructed image obtained by the proposed method are 0.0496 and 0.9435 respectively, and the average reconstruction time is approximately 0.1723s, which is superior to the other three algorithms. The defect reduction degree and reconstruction speed have been significantly improved.

Key words： material defect detection planar electrical capacitance tomography;ECT image reconstruction 1-bit compressed sensing minimax concave penalty non convex algorithm

Received: 29 May 2023 Published: 18 December 2024

PACS:	TB937
	TB973

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2024.12.07 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2024/V45/I12/1797

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